TechBrief — تازه‌ترین اخبار فناوری

Google filters for golf course results are terrible so I built a better way to browse courses using OSM as the backbone.... https://golfcoursebrowser.com/

It's a work in progress and mostly US for now, but I want to expand to the rest of North America, the EU, and the rest of the world ASAP.

It's free, no ads, no login, no bs. If you spot anything wrong (bad info, a missing course, wrong scorecard), you can flag it right on the course page. I actually read those and fix them.

Still a lot of missing info, but I'm filling out more and more each day. The goal is the most complete, and current golf course directory in the world, verified and maintained by actual golfers. I think is attainable in the next few months. The base layer is OpenStreetMap, cross-checked against course websites and enriched with scorecards, USGA rating/slope, and public/private status. User corrections from golfers who know their home course have beaten every commercial data source we check against.

Comments URL: https://news.ycombinator.com/item?id=49054010

Points: 42

# Comments: 7

Show HN: What 180k words look like as a temporal knowledge graph (Oz series)

The graph is free to explore and requires no registration.

SynapTale builds a model of a story as a temporal graph made up of nodes (entities) and edges (their actions and relationships). The graph is not a visualization of the wiki. The wiki, timelines, relationship histories, and analytics are projections of the graph.

The current demo contains 232 entities, 1,852 edges, and a snapshot of the story’s state at every chapter. By chapter 100, it still remembers a promise made in chapter 8 and turns the story into a set of source-verifiable facts.

The most interesting things can be found in the graph itself and in the Analytics tab. A few things I found:

1. The character with the highest kill count is the Tin Woodman—the same character who cries over a beetle he accidentally crushed. Dorothy comes second, with three killing events. 2. Dorothy never deceives anyone during the first 100 chapters of the series. 3. The Scarecrow’s debt to the stork has remained active for 92 chapters, starting in chapter 8. 4. The Cowardly Lion ranks third by number of threats. 5. The first 100 chapters contain 60 secrets and 254 dialogue events.

Technical details

1. Five different multi-agent pipelines combining LLMs and NLP: a prescan, ontology construction, chapter-by-chapter graph extraction, retrospective validation over spans of dozens of chapters, and a linguistic prescan for speech profiles and linguistic edges.

2. A living story needs a living graph. It has to account for time, because entities and the relationships between them evolve. A simple is_active field is not enough.

I ended up with three types of edges:

event: an instantaneous action; identity: a fact; state: a persistent action whose termination requires justification and a supporting quote from the text.

The vast majority of edges are events and end in the same chapter in which they began. This allows the system to scale well, since only a minority of state and identity edges remain continuously active.

3. Ontology. You cannot simply ask an LLM to extract entities and relationships into a graph. With every chapter, even the smartest model will keep inventing unimportant fields, creating new aliases for existing fields, and representing the same fields inconsistently.

Before extracting the graph, the system therefore performs an ontology scan across the entire story. It captures story-specific entity and edge types, along with their fields and descriptions.

4. Epistemics. Events are only one part of a story. It is also important to understand how information is distributed, which is difficult to represent using event edges alone.

I addressed this by introducing a new node type: epistemic nodes, which capture different entities’ perspectives on the same fact. Subtle hints can still be missed, the system is not yet perfect in this area.

Comments URL: https://news.ycombinator.com/item?id=49053986

Points: 8

# Comments: 0

Alien World Chemistry Found Inside Meteorite That Struck New Jersey Home

Article URL: https://www.seti.org/news/alien-world-chemistry-found-inside-meteorite/

Comments URL: https://news.ycombinator.com/item?id=49053708

Points: 9

# Comments: 1

Monday.com is the latest tech company to blame AI for layoffs — here are 20 others

A running look — in reverse chronological order — at the bigger tech companies that have announced significant layoffs this year with AI as a stated factor.

Git rebase -I is not that scary

Article URL: https://cachebag.sh/journal/interactive-rebasing/

Comments URL: https://news.ycombinator.com/item?id=49053385

Points: 37

# Comments: 31

Systems and Delays

Article URL: https://martin.janiczek.cz/2026/07/24/systems-and-delays.html

Comments URL: https://news.ycombinator.com/item?id=49053382

Points: 37

# Comments: 9

Inflect-Micro-v2: complete voice in 9.36M parameters

Article URL: https://huggingface.co/owensong/Inflect-Micro-v2

Comments URL: https://news.ycombinator.com/item?id=49053375

Points: 41

# Comments: 3

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معمولی: گجت‌ها، نرم‌افزار، امنیت، AI، استارتاپ